Onset Detection

Structs

struct OnsetMetric

Distance metrics for onset detection.

The values match FluidOnsetDetection's metric parameter.

Traits: AnyType, Copyable, Deinitable, Equatable, ImplicitlyCopyable, Movable, Writable

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OnsetMetric Functions

struct OnsetMetric . fn write_to

fn write_to Signature

def write_to(self, mut writer: T)

fn write_to Arguments

Name	Type	Default	Description
writer	T	—	—

struct OnsetDetectionFeature

Onset detection feature analysis.

This struct is to be used as the process of a BufferedProcess. It should use WindowType.hann for the input window shape.

This struct creates a time series of spectral differences based on a provided metric.

This struct implements the ten FluidOnsetSlice metrics.

Traits: AnyType, Copyable, Deinitable, FFTProcessable, GetFloat64Featurable, Movable

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OnsetDetectionFeature Functions

struct OnsetDetectionFeature . fn init

Initialize an onset detection function.

fn init Signature

def __init__(out self, metric: OnsetMetric = OnsetMetric.complex_domain, window_size: Int = Int(1024), filter_size: Int = Int(5), frame_delta: Int = Int(0))

fn init Arguments

Name	Type	Default	Description
metric	OnsetMetric	OnsetMetric.complex_domain	The onset metric to calculate.
window_size	Int	Int(1024)	Analysis window size in samples.
filter_size	Int	Int(5)	Median-filter size. Values below 3 use a first difference.
frame_delta	Int	Int(0)	Offset in analysis frames (hops) for Flux, MKL, and Itakura-Saito.

fn init Returns : Self

Static Method

This is a static method.

struct OnsetDetectionFeature . fn get_features

Return the filtered onset detection-function value.

fn get_features Signature

def get_features(self) -> List[Float64]

fn get_features Returns : List[Float64] A one-element List containing the current filtered descriptor value.

struct OnsetDetectionFeature . fn next_frame

Process an unwindowed audio region and return its filtered value.

fn next_frame Signature

def next_frame(mut self, mags: List[Float64], phases: List[Float64])

fn next_frame Arguments

Name	Type	Default	Description
mags	List[Float64]	—	The magnitude spectrum of the input audio frame. This should be a List of Float64 with length equal to window_size // 2 + 1.
phases	List[Float64]	—	The phase spectrum of the input audio frame. This should be a List of Float64 with length equal to window_size // 2 + 1.

struct OnsetDetectionFeature . fn buf_analysis

Analyze a buffer for OnsetDetectionFeature values. The output is a List of Lists, where each inner List contains one Float64 value (the onset detection function value) for each analysis hop.

Note the output is not onset times or a time series of onset triggers. To get onset times or triggers, use OnsetDetection.

fn buf_analysis Signature

def buf_analysis(buf: Buffer, chan: Int = Int(0), start_frame: Int = Int(0), var num_frames: Optional[Int] = None, metric: OnsetMetric = OnsetMetric.complex_domain, window_size: Int = Int(1024), hop_size: Int = Int(512), filter_size: Int = Int(5), frame_delta: Int = Int(0)) -> List[List[Float64]]

fn buf_analysis Arguments

Name	Type	Default	Description
buf	Buffer	—	Source audio buffer.
chan	Int	Int(0)	Source channel to analyze.
start_frame	Int	Int(0)	First frame in the source buffer.
num_frames	Optional[Int]	None	Number of source frames to analyze. A negative value analyzes to the end of the buffer.
metric	OnsetMetric	OnsetMetric.complex_domain	Onset metric to calculate.
window_size	Int	Int(1024)	Analysis window size in samples.
hop_size	Int	Int(512)	Number of samples between analysis frames.
filter_size	Int	Int(5)	Median-filter size.
frame_delta	Int	Int(0)	Offset in analysis frames (hops) used by Flux, MKL, and Itakura-Saito.

fn buf_analysis Returns : List[List[Float64]] One filtered onset detection-function value for each analysis hop.

Raises Error: If onset analysis or buffered processing fails.

Static Method

This is a static method.

struct OnsetDetection

Detect spectral onsets in a time series of audio samples.

This struct implements the ten FluidOnsetSlice metrics.

Traits: AnyType, Copyable, Deinitable, Movable

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OnsetDetection Functions

struct OnsetDetection . fn init

Initialize an onset slicer.

fn init Signature

def __init__(out self, world: Pointer[MMMWorld, MutUntrackedOrigin], metric: OnsetMetric = OnsetMetric.complex_domain, threshold: Float64 = 0.5, debounce: Float64 = 0.10000000000000001, window_size: Int = Int(1024), hop_size: Int = Int(512), filter_size: Int = Int(5), frame_delta: Int = Int(0))

fn init Arguments

Name	Type	Default	Description
world	Pointer[MMMWorld, MutUntrackedOrigin]	—	The MMMWorld used for buffered processing.
metric	OnsetMetric	OnsetMetric.complex_domain	The onset metric to calculate.
threshold	Float64	0.5	Threshold crossing required to emit an onset.
debounce	Float64	0.10000000000000001	Minimum time duration (in seconds) between onsets.
window_size	Int	Int(1024)	Analysis window size in samples.
hop_size	Int	Int(512)	Number of samples between analysis frames.
filter_size	Int	Int(5)	Median-filter size.
frame_delta	Int	Int(0)	Offset in analysis frames (hops) used by Flux, MKL, and Itakura-Saito.

fn init Returns : Self

Static Method

This is a static method.

struct OnsetDetection . fn next

Process one sample and return whether this sample is an onset.

fn next Signature

def next(mut self, input: Float64) -> Bool

fn next Arguments

Name	Type	Default	Description
input	Float64	—	The input audio sample to analyze.

fn next Returns : Bool True if this sample is an onset, False otherwise.

struct OnsetDetection . fn buf_analysis

Return onset sample indices for a buffer.

fn buf_analysis Signature

def buf_analysis(world: Pointer[MMMWorld, MutUntrackedOrigin], buf: Buffer, chan: Int = Int(0), start_frame: Int = Int(0), var num_frames: Optional[Int] = None, metric: OnsetMetric = OnsetMetric.complex_domain, threshold: Float64 = 0.5, debounce: Float64 = 0.10000000000000001, window_size: Int = Int(1024), hop_size: Int = Int(512), filter_size: Int = Int(5), frame_delta: Int = Int(0)) -> List[Int]

fn buf_analysis Arguments

Name	Type	Default	Description
world	Pointer[MMMWorld, MutUntrackedOrigin]	—	The MMMWorld used for buffered processing.
buf	Buffer	—	Source audio buffer.
chan	Int	Int(0)	Source channel to analyze.
start_frame	Int	Int(0)	First frame in the source buffer.
num_frames	Optional[Int]	None	Number of source frames to analyze. A negative value analyzes to the end of the buffer.
metric	OnsetMetric	OnsetMetric.complex_domain	The onset metric to calculate.
threshold	Float64	0.5	Threshold crossing required to emit an onset.
debounce	Float64	0.10000000000000001	Minimum time duration (in seconds) between onsets.
window_size	Int	Int(1024)	Analysis window size in samples.
hop_size	Int	Int(512)	Number of samples between analysis frames.
filter_size	Int	Int(5)	Median-filter size.
frame_delta	Int	Int(0)	Offset in analysis frames (hops) used by Flux, MKL, and Itakura-Saito.

fn buf_analysis Returns : List[Int] A List of Int sample indices where onsets were detected.

Static Method

This is a static method.

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